Accessability of Statistical Software for the Common Fan

It would be easy to think that only business entities with significant capital have the resources to track, record, and analyze large amounts of data. Traditionally it would require organizations to have a player personnel department comprised of individuals with varying jobs ranging from scouts, data miners, and of course personnel directors. The fact is that even though teams are progressively leaning towards implementing their own data analytic departments, a majority of the teams outsource this work through small private companies that specialize in sports data analysis and consultation. Most of the companies are small with limited resources and small staffs. The difference  in the capabilities of the businesses today compared to 20 years ago comes down to progressively accessible and cheap technology. Company's such as DakStats (http://dakststats.daktroniks.com) Sports statistics provide down loadable software packages that can be applied to a number of sports. Available to the public and businesses alike. This software has a multitude of features such as web sync to web casted games and play by play stat tracking. There are also a multitude of web based applications such as Baseball Tracker and Basketball Stat Tracker that provide more limited forms of data tracking and recording. While the apps do not have the ability to analyze data it can be used in conjunction with other statistical software such as (www.minitab.com)  minitab 17 to create comprehensive statistical forecast and reports. The point is with a little knowledge on the interpretation of data an individual could easily analyze data for their own benefit or provide business intelligence as a consulting firm for a sports organization. The profession is not limited to those already within sports organizations and being an expanding field could be the right niche for an aspiring entrepreneur.

Sports Statistics as a Tool for Gambling

As a child growing up the best part of following sports was keeping up with the best players by reviewing their individual stats. I was always aware of the level of competition and what teams had the edge based sole on their individual players. for the most part I generally had an idea of who would win just looking at basic statistical numbers. 40 years ago trading cards where popular amongst kids and young adults. The photo of the player made the card aesthetically pleasing but it was the historical data on the back of the card that made one card more valuable than the next. Essentially the better the numbers on the back of the card the better its monetary value. One could easily review a players track record and forecast future performance. This is applied in today's form of player trading as a new era of stats based virtual player acquisition known as fantasy sports allows fans to create teams using some of the same criteria in much of the same way that a true player personnel director would. Similar to a sports organization fans know that if they can acquire as much talent based on their track record, that their team will perform at a higher level thus adding value to their team. The value added however differs from that of a true sports organization. Virtual teams seek value through earnings that are received through the practice of gambling. Whether placing a wager through a community pool or through online gambling services such as www.fanduel.com, the idea is to invest in players who will provide the highest return. The same holds true in traditional sports betting where bets are placed on teams not only because of team performance but on accumulated talent with proven statistical track records. The most successful gamblers as such is the case with player personnel directors will not only seek to acquire the most obvious players based on hard stats. Keeping in mind that no matter how good a player is they all have strengths and weaknesses. Some have higher statistical numbers in one area and lower numbers in other areas. The key is to create balance that identifies strengths and weaknesses in all players and in turn acquires players that can make up for these differences and complement one another. Although much more thought goes into player acquisition in business, the principles used and risk of the unknown holds true for both. No matter how good the research or reliability of the data, the amount of variables involved are so vast that any pursuit of perfection would always have to be viewed rationally.

Assessing Psychological Factors

As organizations become more dependent on statistical analysis as a means of evaluating player and team p
erformance, a host of other variables will eventually have to be quantified as well. A common practice for all organization within varying industries require some type of employee background investigation to assess a potential employees  mental make up. e.g.
, moral and ethical values and education. This practice is not uncommon within sports organizations, however the value placed on even deeper pyschological factors, such as an individuals disposition, level of intelligence, and emotional stability are not as easily identified or measured. The qualities that forge the make-up of leaders and standout-performers cannot always be identified through statistical data, as many may possess the same measurables but few will actually possess what is often referred to as the "IT" factor.

There are plenty of athletes that have like physical make-ups but generally those who anticipate game play and perform with extreme confidence are the ones who consistently make plays on day to day basis.This is where I feel the over dependence on data analysis in athletic evaluation can lead to managers placing too much value into numbers and devaluing intangibles. Sports data analytics is a growing and evolving field. Those who lead in this field have acknowledged this shortcoming so it is not out of the realm of possibility that these qualities will at one point be measurable as well. One of the recent innovative tools used for accumulating performance data used in the NBA is "Player Tracking". Utilizing strategically placed cameras, player movement on the court and the basketball is tracked 25 times per second giving analytic professionals stats based on speed, distance, player separation, and ball possession. While this type of technology can provide evaluators with an idea of the level of effort and desire a player or team puts out during the course of a game it still is limited in regards to identifying how, when, and why certain athletes can perform under duress while others cannot. The difference between drafting a player number one overall and acquiring a bust or a superstar comes down to one day being able to measure and analyze these traits in the hope of acquiring talent who possess the rare "IT" factor.

Sports and its Dependency on Data Analytics

One of the many reasons why I find sports analysis interesting is the new found acknowledgement of its importance to not only player and team performance but the organizations bottom line. As the money in sports has grown teams have reinvested in their scouting techniques and incorporated data analytic departments as a major component. Statistics have always been used to evaluate talent but over the past 25 years a renewed emphasis has been place on its importance as new and more complex statistical formulas have been developed. Increased revenue and the desire to optimize the cost associated with scouting talent around the world which in many cases begins when players reach the age of 12 has turned talent evaluation into a science. As a business graduate student and avid sports fan I am realizing that their may be a niche that caters to my professional and personal passions. Sports organizations are increasingly operating the player development departments in the same fashion that they operate their other organizational departments. In the past that may have not been the case given that unlike in other industries in sports the product being sold also happens to be the employees. However, the same data driven principles and evaluation techniques used in product placement for example, are starting to be viewed as necessity in an increasingly competitive and lucrative environment. I find that I am drawn to this new practice but with a desire design teams that incorporate relative sports statistical techniques with proven historical practices that are less data driven.

Validity of Statistical Formulas from one Sport to Another

Last week I expressed my opinion on the usefulness of the WAR stat. This week I will continue that theme but with an emphasis on the amount of value a type of stat has in relation from one sport to another. One of my favorite statistical formulas is the defensive and offensive efficiency rating. This particular formula is used for essentially all team sports however my personal opinion is that is more viable for certain sports. Let me explain. The efficiency rating formula is essentially based on possessions and number of points scored or given up per number of possessions. This stat can give an analyst a pretty good estimation on the quality of a teams performance, but first the quantification of what is considered a possession should be easily identifiable and the sample size should be large enough to justify the efficiency rating. For example, in basketball one could easily identify the amount of possessions a team has on a game to game basis, due to the way the game is structured. Each team has 24 seconds to possess and score the ball before possession is transferred. possession are typically conformed without continuous turnover unlike what one would find in a hockey game, and the sample size of possession per game are significant enough to properly analyze a teams effectiveness. In basketball for instance the rating formula is based on every 100 possession a team has the ball or is defending the ball. I think this stat is ideal because possessions are controlled and easily identifiable. In football possession are controlled and identifiable as well, but team efficiency is determined per 100 plays instead of by possession. This method is is a slight alteration from the one used in basketball but it is still ultimately based on possessions.However the difference is in basketball a team is required to score the ball in 24 seconds for every possession. In football their is no requirement to score every play. The dynamic of the sport of football in my opinion limits the viability of this particular formula. Preferably a stat formula such as points per time of possession would accurately describe a football teams efficiency rate. I  I am not insinuating that basketball is the only sport where this statistical formula is useful I am just stating that the formula should be configured accurately to fit the dynamics of a specific sport so that it correlates more effectively to the nature of play. Next post I will discuss how the growing trend of sports statistical analysis is using data as not just a means for developing effective teams but as a method for creating real business intelligence.